A Solo-Based Automated Quality Control Algorithm for Airborne Tail Doppler Radar Data

摘要

An automated quality control preprocessing algorithm for removing nonweather radar echoes in airborne Doppler radar data has been developed. This algorithm can significantly reduce the time and experience level required for interactive radar data editing prior to dual-Doppler wind synthesis or data assimilation. The algorithm uses the editing functions in the Solo software package developed by the National Center for Atmospheric Research to remove noise, Earth-surface, sidelobe, second-trip, and other artifacts. The characteristics of these nonweather radar returns, the algorithm to identify and remove them, and the impacts of applying different threshold levels on wind retrievals are presented. Verification was performed by comparison with published Electra Doppler Radar (ELDORA) datasets that were interactively edited by different experienced radar meteorologists. Four cases consisting primarily of convective echoes from the Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX), Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX), Hurricane Rainband and Intensity Change Experiment (RAINEX), and The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC)/Tropical Cyclone Structure-2008 (TCS08) field experiments were used to test the algorithm using three threshold levels for data removal. The algorithm removes 80%, 90%, or 95% of the nonweather returns and retains 95%, 90%, or 85% of the weather returns on average at the low-, medium-, and high-threshold levels. Increasing the threshold level removes more nonweather echoes at the expense of also removing more weather echoes. The low threshold is recommended when weather retention is the highest priority, and the high threshold is recommended when nonweather removal is the highest priority. The medium threshold is a good compromise between these two priorities and is recommended for general use. Dual-Doppler wind retrievals using the automatically edited data compare well to retrievals from interactively edited data.